Example #1
0
def evaluate(golds, systems, stream, format = "json", trace = False):
  tgn = tsn = tmn = 0;
  tga = tsa = tma = 0;
  tgp = tsp = tmp = 0;
  scores = [];
  result = {"n": 0};
  for gold, system in zip(golds, systems):
    gnames, garguments, gproperties = tuples(gold);
    snames, sarguments, sproperties = tuples(system);
    gn = len(gnames); sn = len(snames);
    mn = len(gnames & snames);
    ga = len(garguments); sa = len(sarguments);
    ma = len(garguments & sarguments);
    gp = len(gproperties); sp = len(sproperties);
    mp = len(gproperties & sproperties);
    tgn += gn; tsn += sn; tmn += mn;
    tga += ga; tsa += sa; tma += ma;
    tgp += gp; tsp += sp; tmp += mp;
    result["n"] += 1;
  p, r, f = fscore(tgn, tsn, tmn);
  result["names"] = {"g": tgn, "s": tsn, "m": tmn, "p": p, "r": r, "f": f};
  p, r, f = fscore(tga, tsa, tma);
  result["arguments"] = {"g": tga, "s": tsa, "m": tma, "p": p, "r": r, "f": f};
  p, r, f = fscore(tgp, tsp, tmp);
  result["properties"] = {"g": tgp, "s": tsp, "m": tmp, "p": p, "r": r, "f": f};
  print(result, file = stream);
Example #2
0
def evaluate(golds, systems, format="json", limit=5, trace=0, useanchor=False):
    if not limit: limit = 5
    tg = ts = tc = n = 0
    gprefix = "g"
    sprefix = "s"
    scores = dict() if trace else None
    for gold, system in intersect(golds, systems):
        id = gold.id
        ginstances, gattributes, grelations, gn = tuples(
            gold, gprefix, useanchor)
        sinstances, sattributes, srelations, sn = tuples(
            system, sprefix, useanchor)
        if trace > 1:
            print("gold instances: {}\ngold attributes: {}\ngold relations: {}"
                  "".format(ginstances, gattributes, grelations))
            print(
                "system instances: {}\nsystem attributes: {}\nsystem relations: {}"
                "".format(sinstances, sattributes, srelations))
        correct, gold, system \
          = get_amr_match(None, None, gold.id, limit = limit,
                          instance1 = ginstances, attributes1 = gattributes,
                          relation1 = grelations, prefix1 = gprefix,
                          instance2 = sinstances, attributes2 = sattributes,
                          relation2 = srelations, prefix2 = sprefix)
        gold -= gn
        system -= sn
        tg += gold
        ts += system
        tc += correct
        n += 1
        if trace:
            if id in scores:
                print("smatch.evaluate(): duplicate graph identifier: {}"
                      "".format(id),
                      file=sys.stderr)
            scores[id] = {
                "g": gold,
                "s": system,
                "c": correct
            }
            if trace > 1:
                p, r, f = fscore(gold, system, correct)
                print("G: {}; S: {}; C: {}; P: {}; R: {}; F: {}"
                      "".format(gold, system, correct, p, r, f),
                      file=sys.stderr)

    p, r, f = fscore(tg, ts, tc)
    result = {
        "n": n,
        "g": tg,
        "s": ts,
        "c": tc,
        "p": p,
        "r": r,
        "f": f
    }
    if trace: result["scores"] = scores
    return result
Example #3
0
def evaluate(golds, systems, format = "json", trace = 0):
  tglp = tslp = tclp = 0;
  tgup = tsup = tcup = 0;
  tglr = tslr = tclr = 0;
  tgur = tsur = tcur = 0;
  tp = tr = 0;
  scores = dict() if trace else None;
  result = {"n": 0, "labeled": dict(), "unlabeled": dict()};

  for gold, system in intersect(golds, systems):
    glprimary, glremote, guprimary, guremote = tuples(gold);
    slprimary, slremote, suprimary, suremote = tuples(system);
    glp = len(glprimary); slp = len(slprimary);
    clp = len(glprimary & slprimary);
    gup = len(guprimary); sup = len(suprimary);
    cup = len(guprimary & suprimary);
    glr = len(glremote); slr = len(slremote);
    clr = len(glremote & slremote);
    gur = len(guremote); sur = len(suremote);
    cur = len(guremote & suremote);
    tglp += glp; tslp += slp; tclp += clp;
    tgup += gup; tsup += sup; tcup += cup;
    tglr += glr; tslr += slr; tclr += clr;
    tgur += gur; tsur += sur; tcur += cur;
    result["n"] += 1;
    if trace:
      if gold.id in scores:
        print("ucca.evaluate(): duplicate graph identifier: {}"
              "".format(gold.id), file = sys.stderr);
      score = {"labeled": dict(), "unlabeled": dict()};
      score["labeled"]["primary"] = {"g": glp, "s": slp, "c": clp};
      score["labeled"]["remote"] = {"g": glr, "s": slr, "c": clr};
      score["unlabeled"]["primary"] = {"g": gup, "s": sup, "c": cup};
      score["unlabeled"]["remote"] = {"g": gur, "s": sur, "c": cur};
      scores[gold.id] = score;
      if trace > 1: print("{}: {}".format(gold.id, score));
  p, r, f = fscore(tglp, tslp, tclp);
  result["labeled"]["primary"] = \
    {"g": tglp, "s": tslp, "c": tclp, "p": p, "r": r, "f": f};
  p, r, f = fscore(tglr, tslr, tclr);
  result["labeled"]["remote"] = \
    {"g": tglr, "s": tslr, "c": tclr, "p": p, "r": r, "f": f};
  p, r, f = fscore(tgup, tsup, tcup);
  result["unlabeled"]["primary"] = \
    {"g": tgup, "s": tsup, "c": tcup, "p": p, "r": r, "f": f};
  p, r, f = fscore(tgur, tsur, tcur);
  result["unlabeled"]["remote"] = \
    {"g": tgur, "s": tsur, "c": tcur, "p": p, "r": r, "f": f};
  if trace: result["scores"] = scores;
  return result;
Example #4
0
 def finalize(counts):
     p, r, f = fscore(counts["g"], counts["s"], counts["c"])
     counts.update({
         "p": p,
         "r": r,
         "f": f
     })
Example #5
0
def evaluate(golds, systems, format = "json", limit = 5, trace = 0):
  if not limit: limit = 5;
  tg = ts = tc = n = 0;
  gprefix = "g"; sprefix = "s";
  scores = dict() if trace else None;
  for gold, system in intersect(golds, systems):
    id = gold.id;
    ginstances, gattributes, grelations = tuples(gold, gprefix);
    sinstances, sattributes, srelations = tuples(system, sprefix);
    correct, gold, system \
      = get_amr_match(None, None, gold.id, limit = limit,
                      instance1 = ginstances, attributes1 = gattributes,
                      relation1 = grelations, prefix1 = gprefix,
                      instance2 = sinstances, attributes2 = sattributes,
                      relation2 = srelations, prefix2 = sprefix);
    tg += gold; ts += system; tc += correct;
    n += 1;
    if trace:
      if id in scores:
        print("smatch.evaluate(): duplicate graph identifier: {}"
              "".format(id), file = sys.stderr);
      scores[id] = {"g": gold, "s": system, "c": correct};
      if trace > 1:
        p, r, f = fscore(gold, system, correct);
        print("G: {}; S: {}; C: {}; P: {}; R: {}; F: {}"
              "".format(gold, system, correct, p, r, f), file = sys.stderr);
        if f != 1.0:
          print("gold instances: {}\ngold attributes {}\ngold relations: {}"
            "".format(ginstances, gattributes, grelations), file=sys.stderr);
          print("system instances: {}\nsystem attributes {}\nsystem relations: {}"
            "".format(sinstances, sattributes, srelations), file=sys.stderr);
    
  p, r, f = fscore(tg, ts, tc);
  result = {"n": n, "g": tg, "s": ts, "c": tc, "p": p, "r": r, "f": f};
  if trace: result["scores"] = scores;
  return result;
Example #6
0
def evaluate(golds, systems, format="json", trace=0):
    tglp = tslp = tclp = 0
    tgup = tsup = tcup = 0
    tglr = tslr = tclr = 0
    tgur = tsur = tcur = 0
    tp = tr = 0
    scores = dict() if trace else None
    result = {
        "n": 0,
        "labeled": dict(),
        "unlabeled": dict()
    }

    for gold, system in intersect(golds, systems):
        glprimary, glremote, guprimary, guremote = tuples(gold)
        slprimary, slremote, suprimary, suremote = tuples(system)
        glp = len(glprimary)
        slp = len(slprimary)
        clp = len(glprimary & slprimary)
        gup = len(guprimary)
        sup = len(suprimary)
        cup = len(guprimary & suprimary)
        glr = len(glremote)
        slr = len(slremote)
        clr = len(glremote & slremote)
        gur = len(guremote)
        sur = len(suremote)
        cur = len(guremote & suremote)
        tglp += glp
        tslp += slp
        tclp += clp
        tgup += gup
        tsup += sup
        tcup += cup
        tglr += glr
        tslr += slr
        tclr += clr
        tgur += gur
        tsur += sur
        tcur += cur
        result["n"] += 1
        if trace:
            if gold.id in scores:
                print("ucca.evaluate(): duplicate graph identifier: {}"
                      "".format(gold.id),
                      file=sys.stderr)
            score = {
                "labeled": dict(),
                "unlabeled": dict()
            }
            score["labeled"]["primary"] = {
                "g": glp,
                "s": slp,
                "c": clp
            }
            score["labeled"]["remote"] = {
                "g": glr,
                "s": slr,
                "c": clr
            }
            score["unlabeled"]["primary"] = {
                "g": gup,
                "s": sup,
                "c": cup
            }
            score["unlabeled"]["remote"] = {
                "g": gur,
                "s": sur,
                "c": cur
            }
            scores[gold.id] = score

    p, r, f = fscore(tglp, tslp, tclp)
    result["labeled"]["primary"] = \
      {"g": tglp, "s": tslp, "c": tclp, "p": p, "r": r, "f": f}
    p, r, f = fscore(tglr, tslr, tclr)
    result["labeled"]["remote"] = \
      {"g": tglr, "s": tslr, "c": tclr, "p": p, "r": r, "f": f}
    p, r, f = fscore(tgup, tsup, tcup)
    result["unlabeled"]["primary"] = \
      {"g": tgup, "s": tsup, "c": tcup, "p": p, "r": r, "f": f}
    p, r, f = fscore(tgur, tsur, tcur)
    result["unlabeled"]["remote"] = \
      {"g": tgur, "s": tsur, "c": tcur, "p": p, "r": r, "f": f}
    if trace: result["scores"] = scores
    return result